系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (6): 1290-1300.doi: 10.3969/j.issn.1001-506X.2020.06.12

• 系统工程 • 上一篇    下一篇

基于合作协同进化的多机空战目标分配

余敏建1(), 嵇慧明1,2(), 韩其松1,*(), 毕伟3()   

  1. 1. 空军工程大学空管领航学院, 陕西 西安 710051
    2. 中国人民解放军94701部队, 安徽 安庆 246000
    3. 中国人民解放军94754部队, 浙江 嘉兴 314000
  • 收稿日期:2019-08-26 出版日期:2020-06-01 发布日期:2020-06-01
  • 通讯作者: 韩其松 E-mail:jhm320826@163.com;lwzy1008@163.com;1165175974@qq.com;1750553694@qq.com
  • 作者简介:余敏建(1963-),男,教授,硕士,主要研究方向为作战领航筹划、航空兵指挥引导自动化。E-mail:jhm320826@163.com|嵇慧明(1994-),男,硕士研究生,主要研究方向为航空兵指挥引导自动化。E-mail:lwzy1008@163.com|毕伟(1984-),男,工程师,主要研究方向为航空兵空战决策与指挥引导对策生成。E-mail:1750553694@qq.com
  • 基金资助:
    国家自然科学基金(61472441);空军工程大学校长基金(XZJY2018030)

Multi-aircraft air combat target allocation based on cooperative co-evolutionary

Minjian YU1(), Huiming JI1,2(), Qisong HAN1,*(), Wei BI3()   

  1. 1. Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China
    2. Unit 94701 of the PLA, Anqing 246000, China
    3. Unit 94754 of the PLA, Jiaxing 314000, China
  • Received:2019-08-26 Online:2020-06-01 Published:2020-06-01
  • Contact: Qisong HAN E-mail:jhm320826@163.com;lwzy1008@163.com;1165175974@qq.com;1750553694@qq.com
  • Supported by:
    国家自然科学基金(61472441);空军工程大学校长基金(XZJY2018030)

摘要:

为寻找一种满足多机空战需求的目标分配优化方法,提升空战效能,提出了一种基于合作协同进化的多机空战目标分配方法。首先,该方法基于单机空战优势,建立多机协同空战优势评价指标体系。然后,对战机间的协同相关性进行分析计算,建立多机协同空战目标分配模型。在变长度染色体遗传算法(genetic algorithm, GA)的基础上,设计了基于交叉、嫁接、分裂和拼接算子的改进合作协同进化算法,提高了模型的进化效率。最后,设计实验分别对优势评价指标体系的有效性、静态算例、动态算例和大规模无人战斗机算例进行仿真验证,并将2种模型以及4种算法的计算结果和所提算法的实验结果进行对比。仿真结果表明,改进合作协同进化算法适用于该模型计算,结果收敛稳定,亲和度值显著提升,能够优化目标分配方案,在空战中具有一定的应用意义。

关键词: 多机空战, 目标分配, 合作协同进化算法, 态势优势, 分配方案

Abstract:

In order to find an optimal target allocation method to meet the requirements of multi-aircraft air combat and improve the air combat efficiency, a multi-aircraft air combat target allocation method based on cooperative co-evolutionary is proposed. Firstly, this method establishes a multi-aircraft cooperative air combat superiority evaluation index system based on single-aircraft air combat superiority. Secondly, the cooperative correlation between aircraft is analyzed and calculated, and a multi-aircraft cooperative air combat target allocation model is established. On the basis of variable length chromosome genetic algorithm(GA), an improved cooperative co-evolutionary algorithm based on crossover, grafting, splitting and splicing operators is designed, which improves the evolution efficiency of the model. Finally, experiments are designed to validate the effectiveness of the superiority evaluation index system, static examples, dynamic examples and large-scale unmanned combat aerial vehicles (UCAV) examples. The results of the two models and four algorithms are compared with the experimental results. The simulation results show that the improved cooperative co-evolutionary algorithm is suitable for the calculation of this model. The convergence is stable and the affinity value is significantly improved. So the target allocation scheme can be optimized and it has certain application significance in air combat.

Key words: multi-aircraft air combat, target allocation, cooperative co-evolutionary algorithm, situation superiority, allocation scheme

中图分类号: